Visualizations are powerful tools that are commonly used by data scientists to get more
insights about their high dimensional data. One can for example cite t-SNE, which is …

Background Epilepsy is a prevalent neurological disorder in which seizures cause recurrent
episodes of unconsciousness or muscle convulsions, seriously affecting the patient's work …

In this work, we propose an interactive visual approach for the exploration and formation of
structural relationships in embeddings of high-dimensional data. These structural …

Existing methods for explaining black box learning models often focus on building local
explanations of the models' behaviour for particular data items. It is possible to create global …

Dimensionality reduction is a crucial area in artificial intelligence that enables the
visualization and analysis of high-dimensional data. The main use of dimensionality …

Dimensionality reduction (DR) is a popular technique that shows great results to analyze
high-dimensional data. Generally, DR is used to produce visualizations in 2 or 3 …

A significant number of studies apply acoustic and linguistic characteristics of human speech
as prominent markers of dementia and depression. However, studies on discriminating …

The visual exploration of high-dimensional (HD) data has gained popularity through the use
of dimensionality reduction (DR) techniques such as t-SNE and UMAP. However, the …

In contrast to classical techniques for exploratory analysis of high-dimensional data sets,
such as principal component analysis (PCA), neighbor embedding (NE) techniques tend to …

The large volume and complexity of medical imaging datasets are bottlenecks for storage,
transmission, and processing. To tackle these challenges, the application of low-rank matrix …